Effective Credit Default Scoring using Anomaly Detection

Krunal Surti; Ashish Patel

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25-Feb-26

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Effective Credit Default Scoring using Anomaly Detection

Author(s):

Krunal Surti , Silver Oak College of Engineering and Technology; Ashish Patel, Silver Oak College of Engineering and Technology

Keywords:

Anomaly Detection, Credit Default, Credit Score, Creditworthiness, Preprocessing, Regression

Abstract:

In recent years there has been a trend towards online purchase so stealing of credit data is high like identity of the credit card owner, password or etc. the attacker may use this data for to take loan from financial domain and they make credit default. Credit scoring is the give the creditworthiness of person. Anomaly Detection is the process of classifies unusual behavior. It is important data analysis task used for classify interesting and emerging patterns, trends and anomalies from data. Anomaly detection is an important tool to detect irregularity in many different domains including financial fraud detection, computer network intrusion, human behavioral analysis and many more. In today’s era the credit and Loan Default is become high because of many fraudulent activity or increase online purchases. To perform anomaly detection in this paper linear regression with rule based classification and logistic regression is used. The preprocessing is used for to perform explore, analyze and determine the factor that play crucial role to find credit default.